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                        数据分析
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                            <b>1.</b>
                        
                        Python数据分析内容
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                            <b>2.1.</b>
                        
                        Python数据课程 软件和环境安装
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                            <b>2.2.</b>
                        
                        python发行版
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                            <b>2.3.</b>
                        
                        交互式编辑器-JupyterNotebook
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                            <b>2.3.1.</b>
                        
                        Jupyter-notebook拓展应用
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                            <b>2.4.</b>
                        
                        包和环境管理器：conda
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                            <b>2.4.1.</b>
                        
                        pip和Virtualenv
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                            <b>2.5.</b>
                        
                        标记语言：Markdown
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                            <b>2.5.1.</b>
                        
                        Markdown语法
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                            <b>2.5.2.</b>
                        
                        文档管理工具-Gitbook
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                            <b>3.</b>
                        
                        数据分析库-Pandas
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                            <b>3.1.</b>
                        
                        pandas
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                            <b>3.2.</b>
                        
                        Series
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                            <b>3.3.</b>
                        
                        DataFrame对象-创建
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            <span><b>4.</b> 数据分析库的操作</span>
            
            
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                            <b>4.1.</b>
                        
                        DataFrame查询1-整体
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                            <b>4.2.</b>
                        
                        DataFrame查询2-专用查询
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                            <b>4.3.</b>
                        
                        DataFrame查询3-专有查询：过滤查询
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                            <b>4.4.</b>
                        
                        Pandas对象的数据操作：增删改查
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                            <b>4.4.1.</b>
                        
                        Pandas数据操作：其他操作
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                            <b>4.4.2.</b>
                        
                        Pandas数据存取
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                            <b>4.4.3.</b>
                        
                        Pandas数据运算
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                            <b>4.4.3.1.</b>
                        
                        Pandas数据运算-拓展
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                            <b>4.4.4.</b>
                        
                        Pandas分组聚合1
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                            <b>4.4.5.</b>
                        
                        Pandas分组聚合2
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                            <b>4.4.6.</b>
                        
                        Pandas数据规整-清理
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                            <b>4.4.7.</b>
                        
                        Pandas数据规整-转换
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                            <b>4.4.7.1.</b>
                        
                        离散化和面元划分
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        <li class="chapter " data-level="4.4.8" data-path="数据分析库的操作/16Pandas数据规整-合并.html">
            
                
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                            <b>4.4.8.</b>
                        
                        Pandas数据规整-合并
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                            <b>4.5.</b>
                        
                        Pandas数据规整-重塑和轴向旋转
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                            <b>4.5.1.</b>
                        
                        透视表和交叉表
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                            <b>5.</b>
                        
                        Python可视化
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                            <b>5.1.</b>
                        
                        基础：Matplotlib常见图表
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                            <b>5.1.1.</b>
                        
                        Matplotlib常见设置和操作
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                            <b>5.2.</b>
                        
                        提升：绘图区域
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                            <b>5.3.</b>
                        
                        提升：绘图组件
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                            <b>5.4.</b>
                        
                        拓展：高级绘图
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                            <b>5.5.</b>
                        
                        拓展：数学计算展示图像
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                            <b>5.6.</b>
                        
                        拓展：注意事项
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                            <b>5.7.</b>
                        
                        拓展：pylab
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                            <b>6.</b>
                        
                        数据分析必备知识点
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        <li class="chapter " data-level="7" data-path="数据分析必备知识点/数据分析流程.html">
            
                
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                            <b>7.</b>
                        
                        数据分析流程
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                        <h1 id="pandas&#x6570;&#x636E;&#x64CD;&#x4F5C;&#xFF1A;&#x5176;&#x4ED6;&#x64CD;&#x4F5C;">Pandas&#x6570;&#x636E;&#x64CD;&#x4F5C;&#xFF1A;&#x5176;&#x4ED6;&#x64CD;&#x4F5C;</h1>
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<li>Pandas&#x5BF9;&#x8C61;&#x7684;&#x547D;&#x540D;&#xFF1A;name</li>
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<h2 id="pandas&#x5BF9;&#x8C61;&#x7684;&#x547D;&#x540D;&#xFF1A;name">Pandas&#x5BF9;&#x8C61;&#x7684;&#x547D;&#x540D;&#xFF1A;name</h2>
<p>Series &#x548C; DataFrame &#x5BF9;&#x8C61;&#x672C;&#x8EAB;&#xFF0C;&#x7D22;&#x5F15;&#x90FD;&#x53EF;&#x4EE5;&#x547D;&#x540D;</p>
<pre><code class="lang-python"><span class="hljs-keyword">import</span> numpy <span class="hljs-keyword">as</span> np
<span class="hljs-keyword">import</span> pandas <span class="hljs-keyword">as</span> pd
</code></pre>
<h1 id="series-&#x7684;name&#x547D;&#x540D;">Series &#x7684;name&#x547D;&#x540D;</h1>
<pre><code class="lang-python">a = pd.Series([<span class="hljs-number">3</span>,<span class="hljs-number">5</span>,<span class="hljs-number">8</span>,<span class="hljs-number">12</span>,<span class="hljs-number">14</span>])
a
</code></pre>
<pre><code>0     3
1     5
2     8
3    12
4    14
dtype: int64
</code></pre><pre><code class="lang-python">a.name  <span class="hljs-comment"># &#x9ED8;&#x8BA4;&#x6CA1;&#x6709;name &#x5C5E;&#x6027;</span>
a.name = <span class="hljs-string">&apos;&#x5F20;&#x4E09;&apos;</span>   <span class="hljs-comment"># &#x5217;&#x7D22;&#x5F15;&#x547D;&#x540D;</span>
a.name
</code></pre>
<pre><code>&apos;&#x5F20;&#x4E09;&apos;
</code></pre><pre><code class="lang-python">a
</code></pre>
<pre><code>0     3
1     5
2     8
3    12
4    14
Name: &#x5F20;&#x4E09;, dtype: int64
</code></pre><h2 id="series&#x7684;&#x547D;&#x540D;">Series&#x7684;&#x547D;&#x540D;</h2>
<pre><code class="lang-python"><span class="hljs-comment"># Series &#x7D22;&#x5F15;&#x547D;&#x540D;</span>


a.index.name 
a.index.name = <span class="hljs-string">&apos;aaa&apos;</span>   <span class="hljs-comment">#&#x884C;&#x7D22;&#x5F15;&#x547D;&#x540D;</span>
a.index
</code></pre>
<pre><code>RangeIndex(start=0, stop=5, step=1, name=&apos;aaa&apos;)
</code></pre><pre><code class="lang-python">a
</code></pre>
<pre><code>aaa
0     3
1     5
2     8
3    12
4    14
Name: &#x5F20;&#x4E09;, dtype: int64
</code></pre><p>Series &#x547D;&#x540D;&#x7684;&#x7528;&#x5904;</p>
<pre><code class="lang-python">a2 = pd.Series([<span class="hljs-number">2</span>,<span class="hljs-number">3</span>,<span class="hljs-number">4</span>,<span class="hljs-number">5</span>,<span class="hljs-number">6</span>])
a2
</code></pre>
<pre><code>0    2
1    3
2    4
3    5
4    6
dtype: int64
</code></pre><pre><code class="lang-python">pd.DataFrame(a2)    <span class="hljs-comment"># Series &#x53D8;&#x6210; DataFrame &#x7684;&#x4E00;&#x5217;&#xFF0C;&#x884C;&#x7D22;&#x5F15;&#x5C31;&#x662F;s&#x7684;&#x7D22;&#x5F15;&#xFF0C;&#x5217;&#x7D22;&#x5F15;&#x5C31;&#x662F;D&#x7684;&#x81EA;&#x589E;&#x7D22;&#x5F15;</span>
</code></pre>
<div>
<style scoped>
    .dataframe tbody tr th:only-of-type {
        vertical-align: middle;
    }

    .dataframe tbody tr th {
        vertical-align: top;
    }

    .dataframe thead th {
        text-align: right;
    }
</style>
<table border="1" class="dataframe">
  <thead>
    <tr style="text-align: right;">
      <th></th>
      <th>0</th>
    </tr>
  </thead>
  <tbody>
    <tr>
      <th>0</th>
      <td>2</td>
    </tr>
    <tr>
      <th>1</th>
      <td>3</td>
    </tr>
    <tr>
      <th>2</th>
      <td>4</td>
    </tr>
    <tr>
      <th>3</th>
      <td>5</td>
    </tr>
    <tr>
      <th>4</th>
      <td>6</td>
    </tr>
  </tbody>
</table>
</div>




<pre><code class="lang-python">a
</code></pre>
<pre><code>aaa
0     3
1     5
2     8
3    12
4    14
Name: &#x5F20;&#x4E09;, dtype: int64
</code></pre><pre><code class="lang-python">pd.DataFrame(a)
<span class="hljs-comment">#&#x5217;&#x7D22;&#x5F15;&#x662F;Series &#x7684;&#x547D;&#x540D;</span>

<span class="hljs-comment"># &#x884C;&#x7D22;&#x5F15;&#x4E5F;&#x6709;&#x540D;&#x5B57;&#xFF1A;Serise &#x7684;index &#x547D;&#x540D;</span>
</code></pre>
<div>
<style scoped>
    .dataframe tbody tr th:only-of-type {
        vertical-align: middle;
    }

    .dataframe tbody tr th {
        vertical-align: top;
    }

    .dataframe thead th {
        text-align: right;
    }
</style>
<table border="1" class="dataframe">
  <thead>
    <tr style="text-align: right;">
      <th></th>
      <th>&#x5F20;&#x4E09;</th>
    </tr>
    <tr>
      <th>aaa</th>
      <th></th>
    </tr>
  </thead>
  <tbody>
    <tr>
      <th>0</th>
      <td>3</td>
    </tr>
    <tr>
      <th>1</th>
      <td>5</td>
    </tr>
    <tr>
      <th>2</th>
      <td>8</td>
    </tr>
    <tr>
      <th>3</th>
      <td>12</td>
    </tr>
    <tr>
      <th>4</th>
      <td>14</td>
    </tr>
  </tbody>
</table>
</div>



<h1 id="dataframe&#x7684;&#x547D;&#x540D;">DataFrame&#x7684;&#x547D;&#x540D;</h1>
<p>&#x5C42;&#x6B21;&#x5316;&#x7D22;&#x5F15;</p>
<pre><code class="lang-python">av = [
    [<span class="hljs-string">&apos;&#x5C0F;&#x660E;&apos;</span>,<span class="hljs-string">&apos;male&apos;</span>,<span class="hljs-number">18</span>,<span class="hljs-number">170</span>,<span class="hljs-number">60</span>,<span class="hljs-string">&apos;&#x5317;&#x4EAC;&#x6D77;&#x6DC0;&apos;</span>,<span class="hljs-number">61</span>],
    [<span class="hljs-string">&apos;&#x5C0F;&#x534E;&apos;</span>,<span class="hljs-string">&apos;female&apos;</span>,<span class="hljs-number">28</span>,<span class="hljs-number">160</span>,<span class="hljs-number">50</span>,<span class="hljs-string">&apos;&#x4E0A;&#x6D77;&#x9759;&#x5B89;&apos;</span>,<span class="hljs-number">74</span>],
    [<span class="hljs-string">&apos;&#x5C0F;&#x7EA2;&apos;</span>,<span class="hljs-string">&apos;female&apos;</span>,<span class="hljs-number">22</span>,<span class="hljs-number">175</span>,<span class="hljs-number">64</span>,<span class="hljs-string">&apos;&#x5E7F;&#x5DDE;&#x5929;&#x6CB3;&apos;</span>,<span class="hljs-number">59</span>],
    [<span class="hljs-string">&apos;&#x5C0F;&#x9751;&apos;</span>,<span class="hljs-string">&apos;male&apos;</span>,<span class="hljs-number">31</span>,<span class="hljs-number">182</span>,<span class="hljs-number">80</span>,<span class="hljs-string">&apos;&#x6DF1;&#x5733;&#x5357;&#x5C71;&apos;</span>,<span class="hljs-number">82</span>],
    [<span class="hljs-string">&apos;&#x5C0F;&#x5170;&apos;</span>,<span class="hljs-string">&apos;female&apos;</span>,<span class="hljs-number">25</span>,<span class="hljs-number">165</span>,<span class="hljs-number">55</span>,<span class="hljs-string">&apos;&#x676D;&#x5DDE;&#x897F;&#x6E56;&apos;</span>,<span class="hljs-number">98</span>],
]
b = pd.DataFrame(
    av,
    index=[<span class="hljs-number">1</span>,<span class="hljs-number">2</span>,<span class="hljs-number">3</span>,<span class="hljs-number">4</span>,<span class="hljs-number">5</span>],
    columns=[<span class="hljs-string">&apos;name&apos;</span>,<span class="hljs-string">&apos;sex&apos;</span>,<span class="hljs-string">&apos;age&apos;</span>,<span class="hljs-string">&apos;heigh&apos;</span>,<span class="hljs-string">&apos;weight&apos;</span>,<span class="hljs-string">&apos;address&apos;</span>,<span class="hljs-string">&apos;grade&apos;</span>]
)
b
</code></pre>
<div>
<style scoped>
    .dataframe tbody tr th:only-of-type {
        vertical-align: middle;
    }

    .dataframe tbody tr th {
        vertical-align: top;
    }

    .dataframe thead th {
        text-align: right;
    }
</style>
<table border="1" class="dataframe">
  <thead>
    <tr style="text-align: right;">
      <th></th>
      <th>name</th>
      <th>sex</th>
      <th>age</th>
      <th>heigh</th>
      <th>weight</th>
      <th>address</th>
      <th>grade</th>
    </tr>
  </thead>
  <tbody>
    <tr>
      <th>1</th>
      <td>&#x5C0F;&#x660E;</td>
      <td>male</td>
      <td>18</td>
      <td>170</td>
      <td>60</td>
      <td>&#x5317;&#x4EAC;&#x6D77;&#x6DC0;</td>
      <td>61</td>
    </tr>
    <tr>
      <th>2</th>
      <td>&#x5C0F;&#x534E;</td>
      <td>female</td>
      <td>28</td>
      <td>160</td>
      <td>50</td>
      <td>&#x4E0A;&#x6D77;&#x9759;&#x5B89;</td>
      <td>74</td>
    </tr>
    <tr>
      <th>3</th>
      <td>&#x5C0F;&#x7EA2;</td>
      <td>female</td>
      <td>22</td>
      <td>175</td>
      <td>64</td>
      <td>&#x5E7F;&#x5DDE;&#x5929;&#x6CB3;</td>
      <td>59</td>
    </tr>
    <tr>
      <th>4</th>
      <td>&#x5C0F;&#x9751;</td>
      <td>male</td>
      <td>31</td>
      <td>182</td>
      <td>80</td>
      <td>&#x6DF1;&#x5733;&#x5357;&#x5C71;</td>
      <td>82</td>
    </tr>
    <tr>
      <th>5</th>
      <td>&#x5C0F;&#x5170;</td>
      <td>female</td>
      <td>25</td>
      <td>165</td>
      <td>55</td>
      <td>&#x676D;&#x5DDE;&#x897F;&#x6E56;</td>
      <td>98</td>
    </tr>
  </tbody>
</table>
</div>




<pre><code class="lang-python"><span class="hljs-comment"># &#x884C;&#x7D22;&#x5F15;&#x547D;&#x540D; </span>

b.index.name 
b.index.name = <span class="hljs-string">&apos;&#x5B66;&#x53F7;&apos;</span>
b
</code></pre>
<div>
<style scoped>
    .dataframe tbody tr th:only-of-type {
        vertical-align: middle;
    }

    .dataframe tbody tr th {
        vertical-align: top;
    }

    .dataframe thead th {
        text-align: right;
    }
</style>
<table border="1" class="dataframe">
  <thead>
    <tr style="text-align: right;">
      <th>&#x5C5E;&#x6027;</th>
      <th>name</th>
      <th>sex</th>
      <th>age</th>
      <th>heigh</th>
      <th>weight</th>
      <th>address</th>
      <th>grade</th>
    </tr>
    <tr>
      <th>&#x5B66;&#x53F7;</th>
      <th></th>
      <th></th>
      <th></th>
      <th></th>
      <th></th>
      <th></th>
      <th></th>
    </tr>
  </thead>
  <tbody>
    <tr>
      <th>1</th>
      <td>&#x5C0F;&#x660E;</td>
      <td>male</td>
      <td>18</td>
      <td>170</td>
      <td>60</td>
      <td>&#x5317;&#x4EAC;&#x6D77;&#x6DC0;</td>
      <td>61</td>
    </tr>
    <tr>
      <th>2</th>
      <td>&#x5C0F;&#x534E;</td>
      <td>female</td>
      <td>28</td>
      <td>160</td>
      <td>50</td>
      <td>&#x4E0A;&#x6D77;&#x9759;&#x5B89;</td>
      <td>74</td>
    </tr>
    <tr>
      <th>3</th>
      <td>&#x5C0F;&#x7EA2;</td>
      <td>female</td>
      <td>22</td>
      <td>175</td>
      <td>64</td>
      <td>&#x5E7F;&#x5DDE;&#x5929;&#x6CB3;</td>
      <td>59</td>
    </tr>
    <tr>
      <th>4</th>
      <td>&#x5C0F;&#x9751;</td>
      <td>male</td>
      <td>31</td>
      <td>182</td>
      <td>80</td>
      <td>&#x6DF1;&#x5733;&#x5357;&#x5C71;</td>
      <td>82</td>
    </tr>
    <tr>
      <th>5</th>
      <td>&#x5C0F;&#x5170;</td>
      <td>female</td>
      <td>25</td>
      <td>165</td>
      <td>55</td>
      <td>&#x676D;&#x5DDE;&#x897F;&#x6E56;</td>
      <td>98</td>
    </tr>
  </tbody>
</table>
</div>




<pre><code class="lang-python"><span class="hljs-comment"># &#x5217;&#x7D22;&#x5F15;&#x547D;&#x540D;</span>
b.columns.name
b.columns.name = <span class="hljs-string">&apos;&#x5C5E;&#x6027;&apos;</span>
b
</code></pre>
<div>
<style scoped>
    .dataframe tbody tr th:only-of-type {
        vertical-align: middle;
    }

    .dataframe tbody tr th {
        vertical-align: top;
    }

    .dataframe thead th {
        text-align: right;
    }
</style>
<table border="1" class="dataframe">
  <thead>
    <tr style="text-align: right;">
      <th>&#x5C5E;&#x6027;</th>
      <th>name</th>
      <th>sex</th>
      <th>age</th>
      <th>heigh</th>
      <th>weight</th>
      <th>address</th>
      <th>grade</th>
    </tr>
    <tr>
      <th>&#x5B66;&#x53F7;</th>
      <th></th>
      <th></th>
      <th></th>
      <th></th>
      <th></th>
      <th></th>
      <th></th>
    </tr>
  </thead>
  <tbody>
    <tr>
      <th>1</th>
      <td>&#x5C0F;&#x660E;</td>
      <td>male</td>
      <td>18</td>
      <td>170</td>
      <td>60</td>
      <td>&#x5317;&#x4EAC;&#x6D77;&#x6DC0;</td>
      <td>61</td>
    </tr>
    <tr>
      <th>2</th>
      <td>&#x5C0F;&#x534E;</td>
      <td>female</td>
      <td>28</td>
      <td>160</td>
      <td>50</td>
      <td>&#x4E0A;&#x6D77;&#x9759;&#x5B89;</td>
      <td>74</td>
    </tr>
    <tr>
      <th>3</th>
      <td>&#x5C0F;&#x7EA2;</td>
      <td>female</td>
      <td>22</td>
      <td>175</td>
      <td>64</td>
      <td>&#x5E7F;&#x5DDE;&#x5929;&#x6CB3;</td>
      <td>59</td>
    </tr>
    <tr>
      <th>4</th>
      <td>&#x5C0F;&#x9751;</td>
      <td>male</td>
      <td>31</td>
      <td>182</td>
      <td>80</td>
      <td>&#x6DF1;&#x5733;&#x5357;&#x5C71;</td>
      <td>82</td>
    </tr>
    <tr>
      <th>5</th>
      <td>&#x5C0F;&#x5170;</td>
      <td>female</td>
      <td>25</td>
      <td>165</td>
      <td>55</td>
      <td>&#x676D;&#x5DDE;&#x897F;&#x6E56;</td>
      <td>98</td>
    </tr>
  </tbody>
</table>
</div>




<pre><code class="lang-python">b.index
</code></pre>
<pre><code>Int64Index([1, 2, 3, 4, 5], dtype=&apos;int64&apos;, name=&apos;&#x5B66;&#x53F7;&apos;)
</code></pre><pre><code class="lang-python">b.columns
</code></pre>
<pre><code>Index([&apos;name&apos;, &apos;sex&apos;, &apos;age&apos;, &apos;heigh&apos;, &apos;weight&apos;, &apos;address&apos;, &apos;grade&apos;], dtype=&apos;object&apos;, name=&apos;&#x5C5E;&#x6027;&apos;)
</code></pre><hr>
<h2 id="pandas-&#x5BF9;&#x8C61;&#x7684;&#x904D;&#x5386;">Pandas &#x5BF9;&#x8C61;&#x7684;&#x904D;&#x5386;</h2>
<hr>
<p>Pandas&#x7684;&#x5BF9;&#x8C61;&#x4E00;&#x822C;&#x4E0D;&#x9700;&#x8981;&#x904D;&#x5386;,&#x5076;&#x5C14;&#x6709;&#x9700;&#x6C42;</p>
<pre><code class="lang-python">a
</code></pre>
<pre><code>aaa
0     3
1     5
2     8
3    12
4    14
Name: &#x5F20;&#x4E09;, dtype: int64
</code></pre><h3 id="series&#x904D;&#x5386;">Series&#x904D;&#x5386;</h3>
<pre><code class="lang-python"><span class="hljs-keyword">for</span> i <span class="hljs-keyword">in</span> a:
    print(i)
</code></pre>
<pre><code>3
5
8
12
14
</code></pre><pre><code class="lang-python">b
</code></pre>
<div>
<style scoped>
    .dataframe tbody tr th:only-of-type {
        vertical-align: middle;
    }

    .dataframe tbody tr th {
        vertical-align: top;
    }

    .dataframe thead th {
        text-align: right;
    }
</style>
<table border="1" class="dataframe">
  <thead>
    <tr style="text-align: right;">
      <th>&#x5C5E;&#x6027;</th>
      <th>name</th>
      <th>sex</th>
      <th>age</th>
      <th>heigh</th>
      <th>weight</th>
      <th>address</th>
      <th>grade</th>
    </tr>
    <tr>
      <th>&#x5B66;&#x53F7;</th>
      <th></th>
      <th></th>
      <th></th>
      <th></th>
      <th></th>
      <th></th>
      <th></th>
    </tr>
  </thead>
  <tbody>
    <tr>
      <th>1</th>
      <td>&#x5C0F;&#x660E;</td>
      <td>male</td>
      <td>18</td>
      <td>170</td>
      <td>60</td>
      <td>&#x5317;&#x4EAC;&#x6D77;&#x6DC0;</td>
      <td>61</td>
    </tr>
    <tr>
      <th>2</th>
      <td>&#x5C0F;&#x534E;</td>
      <td>female</td>
      <td>28</td>
      <td>160</td>
      <td>50</td>
      <td>&#x4E0A;&#x6D77;&#x9759;&#x5B89;</td>
      <td>74</td>
    </tr>
    <tr>
      <th>3</th>
      <td>&#x5C0F;&#x7EA2;</td>
      <td>female</td>
      <td>22</td>
      <td>175</td>
      <td>64</td>
      <td>&#x5E7F;&#x5DDE;&#x5929;&#x6CB3;</td>
      <td>59</td>
    </tr>
    <tr>
      <th>4</th>
      <td>&#x5C0F;&#x9751;</td>
      <td>male</td>
      <td>31</td>
      <td>182</td>
      <td>80</td>
      <td>&#x6DF1;&#x5733;&#x5357;&#x5C71;</td>
      <td>82</td>
    </tr>
    <tr>
      <th>5</th>
      <td>&#x5C0F;&#x5170;</td>
      <td>female</td>
      <td>25</td>
      <td>165</td>
      <td>55</td>
      <td>&#x676D;&#x5DDE;&#x897F;&#x6E56;</td>
      <td>98</td>
    </tr>
  </tbody>
</table>
</div>



<h3 id="dataframe&#x904D;&#x5386;">DataFrame&#x904D;&#x5386;</h3>
<pre><code class="lang-python"><span class="hljs-keyword">for</span> i <span class="hljs-keyword">in</span> b:
    print(i)  <span class="hljs-comment">#&#x5217;&#x7D22;&#x5F15;</span>
</code></pre>
<pre><code>name
sex
age
heigh
weight
address
grade
</code></pre><pre><code class="lang-python"><span class="hljs-keyword">for</span> i <span class="hljs-keyword">in</span> b:
    print(b[i])  <span class="hljs-comment">#&#x5217;&#x503C;</span>
</code></pre>
<pre><code>&#x5B66;&#x53F7;
1    &#x5C0F;&#x660E;
2    &#x5C0F;&#x534E;
3    &#x5C0F;&#x7EA2;
4    &#x5C0F;&#x9751;
5    &#x5C0F;&#x5170;
Name: name, dtype: object
&#x5B66;&#x53F7;
1      male
2    female
3    female
4      male
5    female
Name: sex, dtype: object
&#x5B66;&#x53F7;
1    18
2    28
3    22
4    31
5    25
Name: age, dtype: int64
&#x5B66;&#x53F7;
1    170
2    160
3    175
4    182
5    165
Name: heigh, dtype: int64
&#x5B66;&#x53F7;
1    60
2    50
3    64
4    80
5    55
Name: weight, dtype: int64
&#x5B66;&#x53F7;
1    &#x5317;&#x4EAC;&#x6D77;&#x6DC0;
2    &#x4E0A;&#x6D77;&#x9759;&#x5B89;
3    &#x5E7F;&#x5DDE;&#x5929;&#x6CB3;
4    &#x6DF1;&#x5733;&#x5357;&#x5C71;
5    &#x676D;&#x5DDE;&#x897F;&#x6E56;
Name: address, dtype: object
&#x5B66;&#x53F7;
1    61
2    74
3    59
4    82
5    98
Name: grade, dtype: int64
</code></pre><pre><code class="lang-python"><span class="hljs-keyword">for</span> i <span class="hljs-keyword">in</span> b:
    print(type(b[i]))  <span class="hljs-comment">#&#x5217;&#x503C;&#x4E3A;Series&#x7C7B;&#x578B;</span>
</code></pre>
<pre><code>&lt;class &apos;pandas.core.series.Series&apos;&gt;
&lt;class &apos;pandas.core.series.Series&apos;&gt;
&lt;class &apos;pandas.core.series.Series&apos;&gt;
&lt;class &apos;pandas.core.series.Series&apos;&gt;
&lt;class &apos;pandas.core.series.Series&apos;&gt;
&lt;class &apos;pandas.core.series.Series&apos;&gt;
&lt;class &apos;pandas.core.series.Series&apos;&gt;
</code></pre><pre><code class="lang-python"><span class="hljs-keyword">for</span> i <span class="hljs-keyword">in</span> b:
    <span class="hljs-keyword">for</span> j <span class="hljs-keyword">in</span> b[i]:
        print(j)  <span class="hljs-comment">#&#x5355;&#x5143;&#x683C;&#x503C;</span>
        print(type(j))  <span class="hljs-comment">#&#x5355;&#x503C;</span>
</code></pre>
<pre><code>&#x5C0F;&#x660E;
&lt;class &apos;str&apos;&gt;
&#x5C0F;&#x534E;
&lt;class &apos;str&apos;&gt;
&#x5C0F;&#x7EA2;
&lt;class &apos;str&apos;&gt;
&#x5C0F;&#x9751;
&lt;class &apos;str&apos;&gt;
&#x5C0F;&#x5170;
&lt;class &apos;str&apos;&gt;
male
&lt;class &apos;str&apos;&gt;
female
&lt;class &apos;str&apos;&gt;
female
&lt;class &apos;str&apos;&gt;
male
&lt;class &apos;str&apos;&gt;
female
&lt;class &apos;str&apos;&gt;
18
&lt;class &apos;int&apos;&gt;
28
&lt;class &apos;int&apos;&gt;
22
&lt;class &apos;int&apos;&gt;
31
&lt;class &apos;int&apos;&gt;
25
&lt;class &apos;int&apos;&gt;
170
&lt;class &apos;int&apos;&gt;
160
&lt;class &apos;int&apos;&gt;
175
&lt;class &apos;int&apos;&gt;
182
&lt;class &apos;int&apos;&gt;
165
&lt;class &apos;int&apos;&gt;
60
&lt;class &apos;int&apos;&gt;
50
&lt;class &apos;int&apos;&gt;
64
&lt;class &apos;int&apos;&gt;
80
&lt;class &apos;int&apos;&gt;
55
&lt;class &apos;int&apos;&gt;
&#x5317;&#x4EAC;&#x6D77;&#x6DC0;
&lt;class &apos;str&apos;&gt;
&#x4E0A;&#x6D77;&#x9759;&#x5B89;
&lt;class &apos;str&apos;&gt;
&#x5E7F;&#x5DDE;&#x5929;&#x6CB3;
&lt;class &apos;str&apos;&gt;
&#x6DF1;&#x5733;&#x5357;&#x5C71;
&lt;class &apos;str&apos;&gt;
&#x676D;&#x5DDE;&#x897F;&#x6E56;
&lt;class &apos;str&apos;&gt;
61
&lt;class &apos;int&apos;&gt;
74
&lt;class &apos;int&apos;&gt;
59
&lt;class &apos;int&apos;&gt;
82
&lt;class &apos;int&apos;&gt;
98
&lt;class &apos;int&apos;&gt;
</code></pre><h3 id="&#x7528;pandas&#x4E13;&#x6709;&#x51FD;&#x6570;&#x904D;&#x5386;">&#x7528;Pandas&#x4E13;&#x6709;&#x51FD;&#x6570;&#x904D;&#x5386;</h3>
<pre><code class="lang-python"><span class="hljs-keyword">for</span> index,rows <span class="hljs-keyword">in</span> b.iterrows():
    <span class="hljs-comment">#print(index)   #&#x884C;&#x7D22;&#x5F15;</span>
    <span class="hljs-comment">#print(rows)  #&#x5217;</span>
   <span class="hljs-comment">#print(type(rows))</span>
   <span class="hljs-comment"># print(rows[&apos;name&apos;])  #&#x67E5;&#x8BE2;&#x6307;&#x5B9A;&#x5217;&#x7684;&#x5355;&#x5143;&#x683C;&#x503C;</span>
    <span class="hljs-keyword">for</span> i <span class="hljs-keyword">in</span> rows:
        print(i)  <span class="hljs-comment">#&#x904D;&#x5386;&#x6240;&#x6709;&#x5355;&#x5143;&#x683C;&#x503C;</span>
        <span class="hljs-comment">#print(type(i))</span>
</code></pre>
<pre><code>&#x5C0F;&#x660E;
male
18
170
60
&#x5317;&#x4EAC;&#x6D77;&#x6DC0;
61
&#x5C0F;&#x534E;
female
28
160
50
&#x4E0A;&#x6D77;&#x9759;&#x5B89;
74
&#x5C0F;&#x7EA2;
female
22
175
64
&#x5E7F;&#x5DDE;&#x5929;&#x6CB3;
59
&#x5C0F;&#x9751;
male
31
182
80
&#x6DF1;&#x5733;&#x5357;&#x5C71;
82
&#x5C0F;&#x5170;
female
25
165
55
&#x676D;&#x5DDE;&#x897F;&#x6E56;
98
</code></pre>
                    
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